Semi-local Total Variation for Regularization of Inverse Problems

Laurent Condat (1)

1 GIPSA-AGPIG - GIPSA - Architecture, Géométrie, Perception, Images, Gestes

We propose the discrete semi-local total variation (SLTV) as a new regularization functional for inverse problems in imaging. The SLTV favors piecewise linear images; so the main drawback of the total variation (TV), its clustering effect, is avoided. Recently proposed primal-dual methods allow to solve the corresponding optimization problems as easily and efficiently as with the classical TV.

Mots clés: convex optimization; proximal method; inverse problem; non-local regularization; total variation

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Laurent Condat. Semi-local Total Variation for Regularization of Inverse Problems. EUSIPCO 2014 - 22th European Signal Processing Conference, Sep 2014, Lisbonne, Portugal. ⟨hal-00608693v3⟩